Robust model-based analysis of single-particle tracking experiments with Spot-On.
Elife
; 72018 01 04.
Article
en En
| MEDLINE
| ID: mdl-29300163
ABSTRACT
Single-particle tracking (SPT) has become an important method to bridge biochemistry and cell biology since it allows direct observation of protein binding and diffusion dynamics in live cells. However, accurately inferring information from SPT studies is challenging due to biases in both data analysis and experimental design. To address analysis bias, we introduce 'Spot-On', an intuitive web-interface. Spot-On implements a kinetic modeling framework that accounts for known biases, including molecules moving out-of-focus, and robustly infers diffusion constants and subpopulations from pooled single-molecule trajectories. To minimize inherent experimental biases, we implement and validate stroboscopic photo-activation SPT (spaSPT), which minimizes motion-blur bias and tracking errors. We validate Spot-On using experimentally realistic simulations and show that Spot-On outperforms other methods. We then apply Spot-On to spaSPT data from live mammalian cells spanning a wide range of nuclear dynamics and demonstrate that Spot-On consistently and robustly infers subpopulation fractions and diffusion constants.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Procesamiento de Imagen Asistido por Computador
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Técnicas Citológicas
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Microscopía Intravital
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Imagen Individual de Molécula
Tipo de estudio:
Prognostic_studies
Idioma:
En
Revista:
Elife
Año:
2018
Tipo del documento:
Article
País de afiliación:
Estados Unidos